---
title: "Concepts Overview"
description: "Explore the core ideas and principles behind Superlinked's functionality"
icon: bullseye-arrow
---


1. Describe your data using Python classes with the [@schema](../reference/common/schema/overview) decorator.
2. Describe your vector embeddings from building blocks with [Spaces](../reference/dsl/space/overview).
3. Combine your embeddings into a queryable [Index](../reference/dsl/index/overview).
4. Define your search with dynamic parameters and weights as a [Query](../reference/dsl/query/overview).
5. Load your data using a [Source](../reference/dsl/source/overview).
6. Define your transformations with a [Parser](../reference/common/parser/overview) (e.g.: from [`pd.DataFrame`](../reference/common/parser/dataframe_parser)).
7. Run your configuration with an [Executor](../reference/dsl/executor/overview).

## Colab notebooks explaining the concepts

<CardGroup cols={3}>
<Card 
  title="Accessing stored vector parts" 
  href="https://colab.research.google.com/github/superlinked/superlinked/blob/main/notebook/feature/accessing_stored_vector_parts.ipynb" 
  img="/images/concept-thumbnails/access-vector-parts.png"
>
  Use query interface to return vector-parts based on our needs
</Card>

<Card
  title="Categorical Embeddings"
  href="https://colab.research.google.com/github/superlinked/superlinked/blob/main/notebook/feature/categorical_embedding.ipynb"
  img="/images/concept-thumbnails/Categorical Embeddings.png"
>
  Efficiently represent and compare categorical data in vector space for
  similarity searches.
</Card>

<Card
  title="Combine Multiple Embeddings"
  href="https://colab.research.google.com/github/superlinked/superlinked/blob/main/notebook/feature/combine_multiple_embeddings.ipynb"
  img="/images/concept-thumbnails/Combine Multiple Embeddings.png"
>
  Merge different types of embeddings to create a unified representation for
  complex objects.
</Card>

<Card
  title="Custom Spaces"
  href="https://colab.research.google.com/github/superlinked/superlinked/blob/main/notebook/feature/custom_space.ipynb"
  img="/images/concept-thumbnails/Custom Spaces.png"
>
  Create and manage custom vector spaces for specialized similarity searches.
</Card>

<Card
  title="Dynamic Parameters"
  href="https://colab.research.google.com/github/superlinked/superlinked/blob/main/notebook/feature/dynamic_parameters.ipynb"
  img="/images/concept-thumbnails/Dynamic Parameters.png"
>
  Adjust query parameters dynamically to fine-tune search results.
</Card>

<Card
  title="Event Effects"
  href="https://colab.research.google.com/github/superlinked/superlinked/blob/main/notebook/feature/event_effects.ipynb"
  img="/images/concept-thumbnails/Event Effects.png"
>
  Model and apply the impact of events on vector representations over time.
</Card>

<Card
  title="Hard Filtering"
  href="https://colab.research.google.com/github/superlinked/superlinked/blob/main/notebook/feature/hard_filtering.ipynb"
  img="/images/concept-thumbnails/Hard Filtering.png"
>
  Apply strict criteria to narrow down search results before similarity ranking.
</Card>

<Card
  title="Image Embedding"
  href="https://colab.research.google.com/github/superlinked/superlinked/blob/main/notebook/feature/image_embedding.ipynb"
  img="/images/concept-thumbnails/Image Embedding.png"
>
  Embed text or images into a multi-modal vector space.
</Card>

<Card
  title="Natural Language Querying"
  href="https://colab.research.google.com/github/superlinked/superlinked/blob/main/notebook/feature/natural_language_querying.ipynb"
  img="/images/concept-thumbnails/Natural Language Querying.png"
>
  Perform similarity searches using natural language queries instead of vector
  representations.
</Card>

<Card
  title="Number Embedding Minmax"
  href="https://colab.research.google.com/github/superlinked/superlinked/blob/main/notebook/feature/number_embedding_minmax.ipynb"
  img="/images/concept-thumbnails/Number Embedding Minmax.png"
>
  Embed numerical values within a specified range for effective similarity
  comparisons.
</Card>

<Card
  title="Number Embedding Similar"
  href="https://colab.research.google.com/github/superlinked/superlinked/blob/main/notebook/feature/number_embedding_similar.ipynb"
  img="/images/concept-thumbnails/Number Embedding Similar.png"
>
  Embed numbers to find similar values based on relative closeness rather than
  exact matches.
</Card>

<Card
  title="Optional Schema Fields"
  href="https://colab.research.google.com/github/superlinked/superlinked/blob/main/notebook/feature/optional_schema_fields.ipynb"
  img="/images/concept-thumbnails/optional-schema-fields.png"
>
  Define optional fields in your schema.
</Card>

<Card
  title="Query Result"
  href="https://colab.research.google.com/github/superlinked/superlinked/blob/main/notebook/feature/query_result.ipynb"
  img="/images/concept-thumbnails/query-result.png"
>
  Customize the result object for your queries.
</Card>

<Card
  title="Query Time Weights"
  href="https://colab.research.google.com/github/superlinked/superlinked/blob/main/notebook/feature/query_time_weights.ipynb"
  img="/images/concept-thumbnails/Query Time Weights.png"
>
  Adjust the importance of different embedding components during query
  execution.
</Card>

<Card
  title="Querying Options"
  href="https://colab.research.google.com/github/superlinked/superlinked/blob/main/notebook/feature/querying_options.ipynb"
  img="/images/concept-thumbnails/Querying Options.png"
>
  Customize search behavior with various querying options for refined results.
</Card>

<Card
  title="Recency Embedding"
  href="https://colab.research.google.com/github/superlinked/superlinked/blob/main/notebook/feature/recency_embedding.ipynb"
  img="/images/concept-thumbnails/Recency Embedding.png"
>
  Incorporate time-based relevance into vector representations for up-to-date
  search results.
</Card>

<Card
  title="Text Embedding"
  href="https://colab.research.google.com/github/superlinked/superlinked/blob/main/notebook/feature/text_embedding.ipynb"
  img="/images/concept-thumbnails/Text Embedding.png"
>
  Convert text data into vector representations for semantic similarity
  searches.
</Card>

<Card 
  title="Vector Sampler" 
  href="https://colab.research.google.com/github/superlinked/superlinked/blob/main/notebook/feature/vector_sampler.ipynb" 
  img="/images/concept-thumbnails/Vector Sampling.png"
>
  Generate diverse vector samples to explore and understand the embedding space.
</Card>
</CardGroup>
